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Record W2016949335 · doi:10.1021/ef900313r

Rheological Properties of Nanofiltered Athabasca Bitumen and Maya Crude Oil

2009· article· en· W2016949335 on OpenAlexaffabout
Anwarul Hasan, Michal Fulem, Ala Bazyleva, John M. Shaw

Bibliographic record

VenueEnergy & Fuels · 2009
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAsphalteneAsphaltRheologyOil sandsHydrocarbonChemistryFraction (chemistry)MineralogyViscositySlurryChromatographyOrganic chemistryMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Complex viscosities of Athabasca bitumen (Alberta, Canada) and Maya crude oil (Mexico) samples, along with their permeates and retentates obtained by nanofiltration at 473 K through 5-, 10-, 20-, 50-, and 200-nm ceramic membranes, were investigated over the temperature interval of 298−373 K. The pentane−asphaltene content of the samples varied from 1.5 wt % to 57.2 wt %, whereas the asphaltene-free composition of the samples did not vary from the feed composition (within experimental error). At temperatures of <323 K, part of the maltenes of both of these hydrocarbon resources is solid. The solid maltene fraction is a function of temperature. If this additional solid is taken into account, the experimental relative viscosities for both Athabasca bitumen- and Maya crude-related samples fall on a single master curve, over the entire temperature interval, irrespective of the asphaltene content. The rheological behavior of all feed, permeate, and retentate samples is consistent with that of a slurry that is comprised of a Newtonian liquid plus a dispersed solid that is comprised of noninteracting hard spheres, where the solids fraction is the sum of the solid maltene plus asphaltene mass fractions. Failure to account for solid maltenes in the interpretation of rheological data for these hydrocarbon resources leads to misattributions related to the nature and importance of the role that asphaltenes play in the determination of the complex viscosity of these hydrocarbon resources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.214
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations40
Published2009
Admission routes2
Has abstractyes

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